Local Distribution Fields for Tracking in Complex Scenarios

In order to enhance the performance of distribution fields (DF) based tracking algorithm in complex scenarios, a local distribution field based tracking method is proposed in this paper.Firstly, we randomly crop the whole DF into multiple local DFs.Secondly, based on the principle that larger L₁ distance between foreground DF and background DF can better distinguish foreground from background, some discriminative local DFs are selected.Thirdly, we search the target by a simple gradient descent based on those selected local DFs.Experiment results show that the proposed local DFs method performs better in complex scenarios than the popular DF and multiple instance learning (MIL) tracking algorithms.